Social Sciences

Abstract: While electric vehicles can reduce the environmental impact of CO2, the extent of this effect depends on the growth of the EV market. Growth models, such as the logistic or Gompertz function models, can predict expected EV sales trends. How well these functions predict EV sales has not yet been comprehensively analyzed. To do so, it would be necessary to look into the future to compare today’s predictions with future data. Since this is not possible, this study took a retrograde approach. It went back in time to use the historical data available then to create forecasts that were then compared with the actual values of subsequent years. For example, a forecast based on data from 2010 to 2014 can be compared with the values achieved in subsequent years from 2015 to 2025. The quality of the functions was assessed using fit indices. When comparing 10 different models, the Gompertz function was found to be the most suitable for predicting the EV market.

Abstract: Thailand’s Student Loans Fund (SLF) lends on a mortgage-type basis: borrowers repay fixed, time-escalating fractions of principal regardless of realized income. This paper asks how that design distributes financial stress across borrowers and what it implies for fiscal recovery. Using Mincerian age–earnings functions estimated on the 2022 Thai Labor Force Survey and administrative loan parameters, I build a Monte Carlo microsimulation of 400,000 synthetic borrowers and trace each cohort’s repayment burden, scheduled repayment as a share of annual income, over the fifteen-year term. The step-up schedule raises the median bachelor’s-degree borrower’s burden from about 4 percent of income in the first year to 15 percent in the fifteenth, and to roughly 39 percent for the lowest-earning decile; 35 percent of bachelor’s borrowers, and 65 percent of non-completers, breach a 20 percent severe-burden threshold. This affordability-driven stress is concentrated among low earners and non-completers and is steeply regressive. A counterfactual income-contingent loan caps the burden and removes affordability default, and when appropriately parameterized it recovers as much as the mortgage schedule. A utility-based model shows that aggregate collection follows a Laffer curve in repayment stringency, which income contingency removes. The findings reframe SLF default as a product of loan design rather than borrower irresponsibility.