This paper presents the use of actuarial modeling for the spread of epidemiological diseases. Study is done based on a developed actuarial model of SIR infection which describes the transfer dynamics in an insurance contract in a given population. At the initial stage, we satisfied key assumptions and observed that the rate of infection is positively related and the rate of recovery is negatively related to the level premium payment. Hence, we developed a MATLAB program to calculate the minimum adjusted level premium for a hospitalization plan. Furthermore, this study expanded the basic model to eliminate some problems such as the Vector-Host relationship due to unsatisfied assumptions for the real data. It is reasonable to expand the SIR model by including Vector-Host transfer dynamics to find out an actuarial model for Dengue fever. Accordingly the length of an epidemic season for Dengue over the sample period can be estimated. Results demonstrate no impact from Vector-Host in determining the level premium payment and reveal the possibility of introducing an insurance policy for the spread of Dengue fever in Sri Lanka. Further, as a result, difficulties to clearly identify seasonal patterns of other diseases may also be overcome. We suggest the SIRS infection model with delayed differential equations as an appropriate solution to define an actuarial model for a wide range of diseases.
This study attempts to estimate the share of Sri Lankan shadow economic activities as a percentage of official estimates, while revolving the wheel of non-clarified zones and market functions through overstepping the traditional official estimates. The methodology involves the estimation of structural models to analyse a set of causes of the shadow economy and its influence upon a series of indicators. The study introduces three Multiple Indicator Multiple Cause (MIMIC) models namely MIMIC 5-1-2a, MIMIC 4-1-2b and MIMIC 3-1-3a. The benchmark calculations for each model derives a series of average values for the Sri Lankan shadow economy (SE) in the period from 1990 to2012. Estimated data in model MIMIC 5-1-2a suggests to evidence that the average size of shadow economy in the country is ranging between 91% and 32% in the period from 1990 to 2012 with a decreasing trend. By contrast, calculations for MIMIC 4-1-2b and MIMIC 3-1-3a demonstrate a size of 14% and 52% with an increasing trend respectively. In-depth analysis further reveals the facts that effect the share of tax on goods and services to the government revenue and the level of public employments tend to undermine the increasing pattern of shadow economy. Since the unemployment rate and private employment is playing a charismatic role in the economy, shadow economy tends to increase. Eradicating the workplace enforcement crisis and underemployment issues may hinder the increasing pattern. The results from re-examination of Okun’s law supports for the idea that, less interdependence of the growth of shadow economy and official economy and a parallel growth with shifting stages in market functions.
The study consisted of a survey and field experiment to observe the impact of behavioural nudges on an individual’s attitudes and accuracy on waste sorting. The survey conducted on 203 students of the University of Peradeniya, and then the field experiment within the university premises. The responses to the survey revealed that the participants having a negative attitude toward the usual waste disposal and sorting practices. Also, the majority of the respondents preferred non-monetary incentives as an effective strategy to motivate individuals to improve the accuracy of waste sorting. Then the participants are given nine strategies as separate behavioural nudges to improve the waste sorting behavior. The responses are highly varied and the majority prefer to use a combination of different colours and detailed labels as a motivational strategy. Thus, the preferred strategy was examined at the faculty premises throughout three stages and tested three hypotheses. Findings revealed that the strategy improves the accuracy, and supports the university community for proper waste sorting practices. Further, it exposed that the detail labels and stickers are impactful than the color sensitivity of respondents.
Article History JEL Classification E26, E27, C36 This study refines both theoretical and pragmatic basis in estimating the size of shadow economy in Sri Lanka. Theoretical investigation had noticed a possibility of use the rate of underemployment as a determinant to measure the size of shadow economy. Further it reveals that the relative magnitudes of job finding rate (f) and devaluation in job separation rate (f*) can change the direction of relationship between the rate of underemployment and the size of shadow economy. Empirical investigation with two fitted MIMIC models; MIMIC 5-1-2a and MIMIC 7-1-2 and Benchmark calculations derive a series of average values for Sri Lankan shadow economy for the period 1990-2015. Calculations for both models tend to decrease from 40-50 percent of GDP. Further comparisons express a strong positive relationship between shadow economy with both underemployment and self-employment.Contribution/ Originality: This study contributes the first logical analysis to develop a structural relationship between the rate of underemployment and shadow economy. Further it revivals the depth of Sri Lankan shadow economy as an annual estimations from 1990 to 2015 using standard multivariate analytical techniques.
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