A Silent Crisis: The Impact of Public Health Expenditure on Malnutrition Prevalence in Children Aged Below Five in the Philippines

This study mainly aims to determine whether public health expenditures have been effective in reducing malnutrition among children aged below five in the Philippines. The researchers construct a Grossman (1972) model-based health production function, which treats economic, social, and environmental factors as determinants of nutritional status. OLS estimates show that an increase in food security rates, a decrease in poverty incidence rates, and an increase in the level of urbanization significantly reduce stunting rates. However, no statistically significant relationship exists between the aforementioned independent variables and underweight and wasting rates (aside from the level of urbanization and wasting). In all regression models, the coefficient estimate for public health expenditure is valued near zero and is statistically insignificant, implying that government spending on health has been insubstantial and ineffective in reducing malnutrition prevalence.

When can physical distancing be relaxed? A health production function approach for COVID-19 control policy

Background To assess if physical distancing measures to control the COVID-19 pandemic can be relaxed, one of the key indicators used is the reproduction number R. Many developing countries, however, have limited capacities to estimate R accurately. This study aims to demonstrate how health production function can be used to assess the state of COVID-19 transmission and to determine a risk-based relaxation policy. Methods The author employs a simple “bridge” between epidemiological models and production economics to establish the cumulative number of COVID-19 cases as a short-run total product function and to derive the corresponding marginal product, average product, and production elasticity. Three crucial dates defining the states of transmission, labelled red, yellow, and green zones, are determined. Relaxation policy is illogical in the “red zone” and is not recommended in the “yellow zone”. In the “green zone”, relaxation can be considered. The Bayesian probability of near term’s daily cases meeting a policy target is computed. The method is applied to France, Germany, Italy, the UK, and the US, and to Indonesia as an example of application in developing countries. Results This study uses data from the WHO COVID-19 Dashboard, beginning from the first recording date for each country until February 28, 2021. As of June 30, 2020, France, Germany, Italy, and the UK had arrived at the “green zone” but with a high risk of transmission re-escalations. In the following weeks, their production elasticities were rising, giving a signal of accelerated transmissions. The signal was corroborated by these countries’ rising cases, making them leaving the “green zone” in the later months. By February 28, 2021, the UK had returned to the “green zone”, France, Germany, and Italy were still in the “yellow zone”, while the US reached the “green zone” at a very high number of cases. Despite being in the “red zone”, Indonesia relaxed its distancing measures, causing a sharp rise of cases. Conclusions Health production function can show the state of COVID-19 transmission. A rising production elasticity gives an early warning of transmission escalations. The elasticity is a useful parameter for risk-based relaxation policy.

When can physical distancing be relaxed? A health production function approach for COVID-19 control policy

BackgroundPhysical distancing measures to control the COVID-19 pandemic come at a heavy short-term economic cost. But easing the measures too early carries a high risk of transmission re-escalations. To assess if physical distancing can be relaxed, a number of epidemic indicators are used, most notably the reproduction number R. Many developing countries, however, have limited capacities to estimate R accurately. This study aims to demonstrate how health production function can be used to assess the state of COVID-19 transmission and to determine a risk-based physical distancing relaxation policy.MethodsThe author establishes a short-run health production function, representing the cumulative number of COVID-19 cases, from the standard SIR model. Three zones defining the state of transmission are shown. The probability of meeting a policy target, given a production elasticity range, is computed. The method is applied to France, Germany, Italy, the UK and the US, and to Indonesia as an example of application in developing countries. ResultsAs of June 30, 2020, France, Germany, Italy and the UK have arrived in the “green zone” where relaxation can be considered. The US is still in the “red zone” where physical distancing still needs to be applied. France, Germany and Italy can set a policy target of maximum daily-cases of 500, while the UK has to make do with a target of 1,100 daily-cases. France, Germany, Italy and the UK still exhibit a relatively high risk of their daily-cases failing to meet the policy target or even rising. Indonesia is still in the “red zone”, so it comes as no surprise that the country’s daily-cases rose sharply after relaxation of physical distancing. ConclusionsShort-run health production function can be used to assess the state of COVID-19 transmission and to determine a risk-based physical distancing relaxation policy. Given its simplicity and minimum data requirement, the approach is very useful for developing countries which are unable to have reliable estimates of the reproduction number R. Follow-up research from this study may include estimating an economically optimal date for relaxing distancing measures and application of this method to other epidemics.

A Framework for Assessing Socio-Economic Impact of Covid-19 at Household Level

The governments across the world have adopted measures to contain the spread of virus which has resulted into restricted economic activities. While economic impacts are diverse and wide spread, the interest in examining impacts at household level is of utmost importance from policy perspectives. This helps monitoring the progress of major socio-economic indicators and make timely and appropriate policy responses. In this context, this perspective paper outlines methodology to be adopted in examining the impacts of COVID-19 in number of household level indicators based on the literatures of impact evaluation. This paper also outlines a framework for identifying key priorities areas with particular reference to Nepal. We propose standard household health production function model with a use of quasi-experimental design as a candidate to examine the impacts at the household level. Likewise, indicators pertaining to poverty, food and nutrition, education, health and labor market are of primary interest with reference to Nepal's development aspirations and trajectory. We expect that this paper will contribute in choosing suitable methodology for assessing impacts at household level and understanding the policy and data context in Nepal.

Estimation of a Neonatal Health Production Function for Iran: Secondary Analysis of Iran’s Multiple Indicator Demographic and Health Survey 2010

Background: Despite constant decrease in rate of neonatal mortality, the rate is still higher than that of other under-five children. One of the first steps towards reduction of neonatal mortality is to identify its determinants using health production function. The aim of the present study was to estimate neonatal health production function for Iran. Methods: In this cross-sectional study, Iranian Multiple Indicator Demographic and Health Survey (IrMIDHS) 2010 was used. Four categories of socioeconomic, mother, neonatal demographic and healthcare system factors were entered into the Binomial Logistic Regression model to estimate neonate health production function. Households’ economic status was constructed using principal component analysis. Results: History of abortion/stillbirth had the highest significant positive impact on odds of neonatal mortality (odds ratio=1.98; 95 % CI=1.55-2.75), indicating that neonates of mothers with such a history had 1.98 times higher chance of death compared to other neonates. Moreover, odds ratio of neonatal death for the poorest quintiles was 1.70 (95 % CI=1.08-2.74), indicating that by moving from the poorest quintile to the richest one, the odds of being alive for neonates increased up to 70%. However, skilled birth attendant decreased the chance of death up to 58% (odds ratio=0.58; 95 % CI=0.36-0.93). Conclusion: Considering the most significant inputs of neonatal health production function in Iran, improvement of economic status of households, provision of appropriate care services for mothers, and improvement of delivery care provided by trained personnel, could be priorities for health policymakers to act and reduce neonatal mortality in Iran.

Health expenditures and inequality: a political economy perspective

PurposeThe purpose of this paper is to explore the manner in which the degree of substitutability between public and private health expenditures contributes towards the distribution of wealth and political economy outcomes in the long run.Design/methodology/approachAn overlapping generations model with heterogeneous agents where a person’s probability of survival into old age is determined by a variable elasticity of substitution (VES) health production function with public and private expenditures as inputs is developed. Public expenditure on health is determined through a political economy process.FindingsAnalytical and numerical results reveal that higher substitutability between private and public expenditures at the aggregate level and a higher share of public spending in the production of health lead to higher long run wealth levels and lower inequality. In the political equilibrium, higher aggregate substitutability between public and private health expenditures is associated with more tax revenue allocated towards public health. For most parameter combinations, the political economy and welfare maximising proportions of tax revenue allocated towards public health care converge in the long run.Research limitations/implicationsThe paper is a theoretical investigation of how substitutability between public and private health expenditures affect transitional and long run macroeconomic outcomes. These results are amenable to further empirical investigation.Practical implicationsThe findings indicate that policies to improve institutional aspects that yield higher substitutability between public and private health expenditures and returns to public health spending could lead to better long run economic outcomes.Social implicationsThe results provide a political economy explanation for the low investments in public health care in developing countries, where aggregate substitutability between public and private health expenditures is likely to be lower. Furthermore, comparing the political economy and welfare maximising paradigms broadens the scope of the framework developed herein to provide potential explanations for cross-country differences in health outcomes.Originality/valueThis paper adopts an innovative approach to exploring this issue of substitutability in health expenditures by introducing a VES health production function. In an environment where agents have heterogeneous wealth endowments, this specification enables a distinction to be made between substitutability of these expenditures at the aggregate and individual levels, which introduces a rich set of dynamics that feeds into long run outcomes and political economy results.

Quantifying Air Pollution Vulnerability and its Distributional Consequences

This paper estimates Vulnerability Index of air pollution in Delhi taking into account exposure, susceptibility and coping capacity of households. A general health production function model and a vulnerability assessment framework are used for this purpose. Data was collected through a survey of sample households located in close vicinity to 10 air pollution monitoring stations in Delhi. The estimated vulnerability index is used to show the effect of household exposure to air pollution. The vulnerability index takes into consideration sample households’ socio-economic status, demographic profile and other characteristics. Result showed that households of lower socio-economic status were the most vulnerable to air pollution and its consequences. The study also quantifies the economic benefits to Delhi households from reduction in air pollution to the standard safety limits of PM10 (100 µg/m3). Estimates show that the total annual economic (health) benefits for a typical household is Rs. 33,978 and for the whole population of Delhi is Rs. 52.4 billion. The study also found that a household of a lower socio-economic status could save much more out of their annual income (4.96 per cent) as compared to a household of a higher socio-economic status (1.97 per cent) from reduced air pollution.