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Child mortality rates are related to factors that are likely to impact a population’s health as well as the level of economic development, standards of living, and social welfare. Among all the factors associated with child mortality, women-related factor, such as literacy and labour market participation have been the single most important factor in reducing child mortality. While general economic development influences death rates, mortality rates also affect the level of economic development. This paper analyses the relationship between economic development and child mortality, along with the effects of income inequality, fertility, female literacy and female labour force participation rates. To consider this endogenous relationship, this paper uses a cross-country panel data - across countries and over time - for 85 countries for two years 2000 and 2022, applying the panel fixed effects instrumental variable estimation method. Empirical estimates show that there exists a significant positive effect of fertility and a sizable negative effect of per capita income and female literacy on child mortality, while income inequality and female labour force participation play not so important for controlling child mortality across countries and over time.

Keywords: child mortality, fertility, income, income inequality, female literacy, female labour force participation, panel fixed effects instrumental variable estimation

Agricultural development is not only depending on just adoption of technological innovations but also by the efficient use of inputs through innovations. In Telangana, majority of populations depends on agriculture for their livelihoods. Paddy is the major crop and mostly it is cultivated under lift irrigation (tube wells and bore wells). Therefore, lift irrigation led to an additional monetary burden to the farmers and also it has devastating effects on the environment. In this context, system of rice intensification (SRI) is necessary to solve all these problems because it produces yield by using less inputs especially water and this led to efficiency in inputs use. SRI is based on fewcomponents that interact with each other; early and healthy establishment, reduced plant density, improved soil conditions through weeding, and reduced and control water application. According to literature, SRI claimed higher benefits to the farmers by using lesser inputs. Therefore, the paper intends to study the economic, technical and allocative efficiency of the SRI farmers and determinants of these efficiency. SRI farming households and non-SRI farming households from seven villages from central Telangana for the season kharif 2017 have been surveyed. Data on inputs and output (physical and monetary terms) has been collected through the structural pre-tested questionnaires. The stochastic production frontier has been used to analyze the efficiency of the SRI farmers. The study revealed that SRI farmers found to be more efficient compared to the non-SRI farmers. Moreover, among the SRI farmers, early adopters of SRI gained higher efficiencies. Age of the farmer, their family size, education of the farmer and farming experience are the significant determining factors for the higher efficiencies among the SRI farmers. 

Keywords: Adoption of SRI, Stochastic production function, efficiency and determinants of efficiency.

Comprehending the influence of weather conditions on vehicular traffic crashes might facilitate the formulation of focused measures and regulations intended to mitigate incidents and enhance traffic security. The purpose of this study is to investigate the short- and long-term effects of weather conditions on Nigerian traffic accidents. We used information from the Federal Road Safety Corps (FRSC), the National Bureau of Statistics (NBS), and the Nigerian Meteorological Agency (NIMET). To evaluate the spatial short and long time association between meteorological conditions and traffic crashes, an autoregressive distributed lag model is used. The findings indicate that there is a positive and significant long-term relationship between temperature, rainfall, and cloud cover and the number of road crashes in Nigeria. However, in the short term, only temperature and rainfall showed a positive and significant relationship; evaporation, relative humidity, and cloud cover showed a negative and insignificant relationship with road accidents in Nigeria. For everyone who uses the roads and travels, including government agencies, groups dedicated to road safety, insurance providers, and the general public, this study is extremely important. In the end, it can save lives and lessen the financial damages brought on by traffic accidents by teaching drivers safe behaviors to follow in inclement weather.

Keyword: Climate; Weather; Transportation, Road Accident; ARDL Model; Error Correction Mechanism (ECM)

Economic policy changes affect the economy through multiple channels and the channel effects vary. The central bank monetary policy aims to control the output and prices through money and capital markets. The monetary transmission channels are the interest rate, credit, exchange rate and asset price channels through which monetary shock propagates to the real economy.

This paper examines the relative strengths of the monetary transmission channels in India from 2000Q1 to 2023Q4 using quarterly data applying the structural vector autoregression estimation method. The estimated results the significance of interest rate and asset price channels in transmitting monetary shocks to the real economy in India, while credit and exchange rate channels are weak. A disaggregated analysis of the components of aggregate demand shows that the maximum impact is borne by investment demand and imports. Variance decomposition analysis indicates that interest rate accounts for a significant percentage of the fluctuations in the components of aggregate demand, except private consumption. Robustness checks show that all the channels of monetary policy are robust and all the components of aggregate demand except for private consumption are robust around the period where the impacts are felt the most.

Keywords: Monetary policy, transmission channels, interest rate, credit, asset price, exchange rate, aggregate demand, SVAR estimation

Using propensity scores as covariates can control the effect of confounders in observational studies. However, the methods of variable selection for propensity score modeling are still under debate. To gain insight on the variables that should be used in the propensity model, a simulation study with randomly generated scenarios was conducted to examine confounding variables with varying effect sizes on exposure and outcome. We found that there was a negative effect for including variables related to exposure but not outcome (aka instrumental variables). The inclusion of variables related to outcome, but not related to exposure has little to no detrimental effect on the propensity model. All other relationships did not have an appreciable negative effect either. However, including variables related to both exposure and outcome is necessary for a strong propensity model. Therefore, we recommend including all possible confounders except instrumental variables into the propensity model. In terms of hypothesis testing, we recommend inclusion of all possible confounders to avoid inflation of type I error rates.

Keywords: Observational Studies, Propensity Scores, Logistic Regression