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Impact Of Socio-Economic Factors And Social Affiliation On Living Standards: A Quantile Regression Approach Impact Of Socio-Economic Factors And Social Affiliation On Living Standards: A Quantile Regression Approach, Renuka Mahadevan, Sandy Suardi
Impact Of Socio-Economic Factors And Social Affiliation On Living Standards: A Quantile Regression Approach Impact Of Socio-Economic Factors And Social Affiliation On Living Standards: A Quantile Regression Approach, Renuka Mahadevan, Sandy Suardi
Sandy Suardi
The influence of socio-economic factors and social affiliation on living standards is shown to be contingent on the living standard status of the household. This new result casts doubt on studies that use conditional mean regression analysis and the Oaxaca-Blinder decomposition analysis to study the impact of 'characteristics' and 'structural' components in areas such as poverty, health and labour market outcomes.
Minimum Wages And Employment: Reconsidering The Use Of A Time Series Approach As An Evaluation Tool, Wang-Sheng Lee, Sandy Suardi
Minimum Wages And Employment: Reconsidering The Use Of A Time Series Approach As An Evaluation Tool, Wang-Sheng Lee, Sandy Suardi
Sandy Suardi
The time series approach used in the minimum wage literature essentially aims to estimate a treatment effect of increasing the minimum wage. In this article, we employ a novel approach based on aggregate time series data that allows us to determine if minimum wage changes have significant effects on employment. This involves the use of tests for structural breaks as a device for identifying discontinuities in the data, which potentially represent treatment effects. In an application based on Australian data, the tentative conclusion is that the introduction of minimum wage legislation in Australia in 1997 and subsequent minimum wage increases …
Modelling And Forecasting Short-Term Interest Rate Volatility: A Semiparametric Approach, Aijun Hou, Sandy Suardi
Modelling And Forecasting Short-Term Interest Rate Volatility: A Semiparametric Approach, Aijun Hou, Sandy Suardi
Sandy Suardi
This paper employs a semiparametric procedure to estimate the diffusion process of short-term interest rates. The Monte Carlo study shows that the semiparametric approach produces more accurate volatility estimates than models that accommodate asymmetry, level effect and serial dependence in the conditional variance. Moreover, the semiparametric approach yields robust volatility estimates even if the short rate drift function and the underlying innovation distribution are misspecified. Empirical investigation with the U.S. three-month Treasury bill rates suggests that the semiparametric procedure produces superior in-sample and out-of-sample forecast of short rate changes volatility compared with the widely used single-factor diffusion models. This forecast …